Image Enhancement of Restored Motion Blurred Images

Motion blurred images could be restored by Super-Resolution arithmetic which took the angle calculated by Radon transformation of the spectrum of original images and the extent calculated by autocorrelation as parameters necessarily even though the blur of images was very severity. Unfortunately the noise of blurred images would be amplified while we captured useful information, which influenced the observation of restored images seriously. An enhancement arithmetic was proposed in this discourse to improve the quality of the low signal-noise ratio images obtained through restoration arithmetic. The main purpose of the arithmetic was to eliminate unwanted noises and remain desired signals. The arithmetic was based on the principle of the least square error method, which fitted discrete pixels to continuous piecewise curves. The interval of each row and column was subdivided into several subintervals to predigest the fitting of pixels. Then a curve was used to fit the pixels within the subinterval. A weighting technique with a linear weighting factor was proposed to merge two adjacent lines together. A series of experiments were carried out to research the effects of the arithmetic, and the signal-noise ratio showed that the proposed arithmetic could achieve high quality enhancement images.